A Mathematician at the Ballpark: Odds and Probabilities for Baseball Fans

Ken Ross, a former President of the Mathematical Association of America and a lifelong student of baseball, has written a lively and highly illuminating account of the mathematics of baseball. Ross uses a rich collection of examples populated by real players to illustrate mathematical ideas that are being used with increasing frequency by more and more teams. Starting with Batting Average (AVG), that most basic of baseball terms, he soon has the reader appreciating Total Bases (TB), Slugging Percentage (SLG), On - Base Percentage (OBP), and BRA. Ross is likely to surprise you, too, with the following puzzler: In 1995, Derek Jeter's AVG was .250 and David Justice's AVG was .253. In 1996, Jeter's AVG was .314 and Justice's AVG was .321. Based on batting averages alone, you'd probably guess that Justice did better than Jeter over those two years. That guess is wrong. Read Mathematician at the Ballpark if you want to see why. He next introduces a bit of elementary probability and explains how he used it in developing his own 'system' for betting on games. What is especially interesting about his system is it's reliance on betting on the underdog. He follows, some might say of necessity, with great chapters titled When to Stop Betting and Streaks. Ross is a gifted writer who really knows baseball and mathematics. You will apprciate both subjects a lot more after reading his book.

This cheerful and meticulous little volume uses baseball as a medium for introducing clear, mathematically correct thinking about probability and statistics to high school and college students. What stands out most about Ross' writing are: (1) his ability to express his love for his subjects (math and baseball) in a dignified way, and (2) the clarity of the presentation. If you are interested in a more hard-core sabremetrics dissertation that deeply probes the limits to what mathematics can reveal about baseball, you are looking in the wrong place. However, if you want to learn (or teach) basic concepts of probability and a correct understanding of random processes to add a new dimension your enjoyment of baseball (and understanding of the world in general), this book is a great place to start.

This is a wonderful little book! It gently introduces many of the basics of probability using baseball as a context. The author is a retired mathematician who learned to love numbers and probability through baseball. This book would be great for a bright kid (or anyone) who loves baseball but thinks math is boring. The author writes in a very friendly style, making things simple without being condescending.

This book gives a gentle introduction to probability and odds. It's not a statistics text and doesn't pretend to be one, though the last chapter discusses some questions that can really only be answered using statistical methods. The author makes it clear that the models he discusses, and often illustrates with familiar examples, are only approximations to real-world baseball (if there is such a thing). There's genuine math, presented in an engagingly informal style at about a high school level. Not enough to guarantee the reader will win at sports gambling, but enough to give a feeling for how the pros might do it. Along the way, there are tidbits of baseball lore salted with the author's frankly personal opinions.

Nowhere does one find more recorded statistical data than in and around baseball. Seemingly everything gets measured and recorded. I found this delightful book last week at a mathematics conference and looked through it because of its combination of a chatty style and no shyness about describing the mathematics of probabilities and odds computations. So I bought the book -- and I found myself reading it through in a sitting! I have read several other popularizations of statistics as applied to baseball, but I've not seen any with the clarity and focused precision Ken Ross has lovingly put into this book. Precisely because baseball has evolved into such a rich combination of strategy and tactics, Ross knows from his teaching experience that novices need to build up a good understanding of less complex applications of probability theory prior to looking at direct applications to the richness of baseball. In this book, he has repeatedly achieved a fine balance of showing the theory, its application to a gambling application, and then to a related baseball context. (Probablility theory originated in work done by Blaise Pascal, Leonhard Euler and Joseph-Louis LaGrange specifically to compute gambling odds.) Starting with how to interpret averages to identify the best hitter of all time, Ross takes us through how to determine the probable behavior of a player or team and how to calculate the probability that a World Series willl go four, five, six or seven games. There are a lot of useful tools in this little book, and its strength is in the cheerful way it tells us how to learn to use them. All the tools that are needed to go on to deeper study (and application!) are provided, along with an annotated bibliography and pointers to SABR. This book would make a splendid gift for a young boy or girl who likes mathematics and sports!